Based on panel data from 2000 to 2017 in 29 Chinese provinces, this paper analyzes the impact of industrial structure upgrading on carbon emissions by constructing a spatial panel model and a panel threshold model. The results show that (1) there is a significant spatial correlation between carbon emissions in Chinese provinces, and the carbon emissions of a province are affected by the carbon emissions of surrounding provinces; (2) in China, carbon emissions have a significant time lag feature, and current carbon emissions are largely affected by previous carbon emissions; (3) industrial structure upgrading can effectively promote carbon emission reductions in local areas, and the impact of industrial structure upgrading on carbon emissions has a significant threshold effect. With continued economic development, the promotion effect of industrial structure upgrading on carbon emission reductions will decrease slightly, but this carbon emission reduction effect is still significant. (4) In addition, there is a clear difference between the impact of energy consumption intensity and population size on carbon emissions in short and long terms. In the short term, the increase in energy consumption intensity and the expansion of population size not only increase the carbon emissions of a local area but also increase the carbon emissions of neighboring areas. In the long term, the impact of energy consumption intensity and population size on carbon emissions of neighboring areas will be weakened, but the promotion impact on carbon emissions in local areas will be strengthened.

Using panel data for 29 provinces in China from 2000 to 2018, this paper mainly presents an empirical study on the impact of industrial structure upgrades on the urban–rural income gap. An overall analysis at the national level is conducted before the separate analysis of the relevant content of China's eastern, central, and western regions. The results reveal that at the national level, the upgrading of industrial structure is conducive to narrowing the urban–rural income gap; however, the impact of industrial structure upgrades on the urban–rural income gap differs from different regions: in eastern China, the impact of industrial structure upgrades on the urban–rural income gap varies over time, and the relationship between the two variables shows an N‐shaped curve; in central China, the upgrading of industrial structure can help to narrow the income gap between urban and rural areas; in western China, upgrading the industrial structure will widen the urban–rural income gap. Finally, certain policy recommendations are proposed.